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Real-time Analytics with Storm and Cassandra

You're reading from  Real-time Analytics with Storm and Cassandra

Product type Book
Published in Mar 2015
Publisher
ISBN-13 9781784395490
Pages 220 pages
Edition 1st Edition
Languages
Author (1):
Shilpi Saxena Shilpi Saxena
Profile icon Shilpi Saxena
Toc

Table of Contents (19) Chapters close

Real-time Analytics with Storm and Cassandra
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Let's Understand Storm 2. Getting Started with Your First Topology 3. Understanding Storm Internals by Examples 4. Storm in a Clustered Mode 5. Storm High Availability and Failover 6. Adding NoSQL Persistence to Storm 7. Cassandra Partitioning, High Availability, and Consistency 8. Cassandra Management and Maintenance 9. Storm Management and Maintenance 10. Advance Concepts in Storm 11. Distributed Cache and CEP with Storm Quiz Answers Index

Consistent hashing


Before you understand its implication and application in Cassandra, let's understand consistent hashing as a concept.

Consistent hashing works on the concept in its name—that is hashing and as we know, for a said hashing algorithm, the same key will always return the same hash code—thus, making the approach pretty deterministic by nature and implementation. When we use this approach for sharding or dividing the keys across the nodes in the cluster, consistent hashing is the technique that determines which node is stored in which node in the cluster.

Have a look at the following diagram to understand the concept of consistent hashing; imagine that the ring depicted in the following diagram represents the Cassandra ring and the nodes are marked here in letters along with the numerals that actually mark the objects (inverted triangles) to be mapped to the ring.

Consistent hashing for the Cassandra cluster

To compute the ownership of the object to the node it belongs to, all...

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